metobs_toolkit.sensordata.SensorData#

class SensorData(stationname: str, datarecords: np.ndarray, timestamps: np.ndarray, obstype: Obstype, datadtype: type = <class 'numpy.float32'>, timestamps_tz: Union[tzfile | tzinfo | str] = 'UTC', **setupkwargs)[source]#

Holds data for one station for one sensor.

Parameters:

stationname (str) – Name of the station.
datarecords (np.ndarray) – Array of data records.
timestamps (np.ndarray) – Array of timestamps.
obstype (Obstype) – Observation type.
datadtype (type, optional) – Data type of the records, by default np.float32.
timezone (str or tzinfo, optional) – Timezone identifier for the timestamps (e.g., ‘UTC’, ‘Europe/Amsterdam’), by default ‘UTC’.
freq_estimation_method ({'highest', 'median'}, optional) – Method to estimate frequency, by default ‘median’.
freq_estimation_simplify_tolerance (pandas.Timedelta or str, optional) – Tolerance for frequency estimation simplification, by default pandas.Timedelta(‘1min’).
origin_simplify_tolerance (pandas.Timedelta or str, optional) – Tolerance for origin simplification, by default pandas.Timedelta(‘1min’).
timestamp_tolerance (pandas.Timedelta or str, optional) – Tolerance for timestamp matching, by default pandas.Timedelta(‘4min’).

__init__(stationname: str, datarecords: np.ndarray, timestamps: np.ndarray, obstype: Obstype, datadtype: type = <class 'numpy.float32'>, timestamps_tz: Union[tzfile | tzinfo | str] = 'UTC', **setupkwargs)[source]#

Initialize SensorData for a single station and observation type.

Parameters:

stationname (str) – Name of the station this sensor belongs to.
datarecords (numpy.ndarray) – Raw observation values. Will be stored after unit conversion during setup.
timestamps (numpy.ndarray) – Timestamps corresponding to datarecords.
obstype (Obstype) – Observation type describing the measured variable and its units.
datadtype (type, optional) – Numeric dtype for the stored series. Default is numpy.float32.
timestamps_tz (str or tzinfo, optional) – Timezone of the provided timestamps. Default is 'UTC'.
**setupkwargs – Additional keyword arguments forwarded to _setup (e.g. freq_estimation_method, timestamp_tolerance).

Methods

`__init__`(stationname, datarecords, ...[, ...])	Initialize SensorData for a single station and observation type.
`convert_outliers_to_gaps`()	Convert all outliers to gaps.
`convert_to_standard_units`()	Convert the data records to the standard units defined in the observation type.
`copy`([deep])	Return a copy of the sensordata.
`duplicated_timestamp_check`()	Check for duplicated timestamps in the series.
`fill_gap_with_modeldata`(modeltimeseries[, ...])	Fill gaps using model data.
`gap_overview_df`()	Create gap status overview DataFrame with one row per gap period.
`get_info`([printout])	Retrieve and optionally print basic information about the sensor data.
`get_qc_freq_statistics`()	Generate quality control (QC) frequency statistics.
`gross_value_check`(**qckwargs)	Perform a gross value check on the series.
`interpolate_gaps`([method, ...])	Interpolate gaps in the data.
`pd_plot`([show_labels])	A wrapper on the pandas.series.plot function for SensorData.
`persistence_check`(**qckwargs)	Perform a persistence check on the series.
`qc_overview_df`()	Build a QC overview DataFrame for a single SensorData object.
`repetitions_check`(**qckwargs)	Perform a repetitions check on the series.
`resample`(target_freq[, shift_tolerance, ...])	Resample to a new time resolution.
`step_check`(**qckwargs)	Perform a step check on the series.
`to_xr`()	Convert Sensordata (observations, including labels) to an xarray.Dataset.
`window_variation_check`(**qckwargs)	Perform a window variation check on the series.

Attributes

`df`	SensorData DataFrame constructor.
`end_datetime`	Return the end datetime of the series.
`freq`	Return the frequency of the series.
`gapsdf`	Return a DataFrame of the gap records.
`outliersdf`	Return a DataFrame of the outlier records.
`start_datetime`	Return the start datetime of the series.
`stationname`	Return the name of the station this SensorData belongs to.
`tz`	Return the timezone of the stored timestamps.